![]() ![]() After that, you can make predictions and display them using Detectron's Visualizer utility. You only need to load in a config and some weights and then create a DefaultPredictor. Using a pre-trained model is super easy in Detectron2. If you're interested, you can find the files on my Github. If you want to run Detectron2 with Docker, you can find a Dockerfile and docker-compose.yml file in the docker directory of the repository.įor those of you who also want to use Jupyter notebooks inside their container, I created a custom Docker configuration, which automatically starts Jupyter after running the container. Docker is great because you don't need to install anything locally, which allows you to keep your machine nice and clean. Install using DockerĪnother great way to install Detectron2 is by using Docker. ![]() However, if you are experiencing any errors, take a look at the Common Installation Issues section of the official installation guide. #!pip install detectron2 -f " depending on your CUDA version or "cpu" if you don't have a GPU.įor most machines, this installation should work fine. # Install pre-built detectron2 that matches pytorch version, if released: # Detectron2 has not released pre-built binaries for the latest pytorch () ![]() If you are working in Google Colab, it can be installed with the following four lines: !python -m pip install pyyaml=5.1 Installing Detectron2 is easy compared to other object detection frameworks like the Tensorflow Object Detection API. You can find all the code covered in the article on my Github. This article will help you get started with Detectron2 by learning how to use a pre-trained model for inferences and how to train your own model. ![]() The new framework is called Detectron2 and is now implemented in PyTorch instead of Caffe2.ĭetectron2 allows us to easily use and build object detection models. (Tested on Linux and Windows)Īlongside PyTorch version 1.3, Facebook also released a ground-up rewrite of their object detection framework Detectron. Update Feb/2020: Facebook Research released pre-built Detectron2 versions, making local installation a lot easier. ![]()
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